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此仓库是为了提升国内下载速度的镜像仓库,每日同步一次。 原始仓库: https://github.com/Zackriya-Solutions/meeting-minutes
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README

Meeting Minutes - Rust Implementation (Experimental)

This is an experimental Rust-based implementation of the Meeting Minutes AI assistant, located in the /experiment directory of the main project. It aims to provide better performance and native integration compared to the main implementation.

Features

  • Real-time audio recording from both microphone and system audio
  • Live transcription using Whisper ASR (locally running)
  • Native desktop integration using Tauri instead of Electron
  • Speaker diarization support
  • Rich text editor for note-taking
  • Privacy-focused: All processing happens locally

Prerequisites

  • Node.js (v18 or later)
  • Rust (latest stable)
  • pnpm (v8 or later)
  • macOS (for system audio capture)
  • Xcode Command Line Tools

Project Structure

The main project structure is:

/meeting-minutes
├── backend/          # Main Python backend
├── docs/            # Project documentation
├── frontend/        # Main Electron frontend
└── experiment/      # Experimental implementations
    ├── rust_based_implementation/  # This implementation
    │   ├── src/                   # Next.js frontend
    │   ├── src-tauri/             # Rust backend
    │   └── whisper-server-package/ # Local transcription server
    ├── screenpipe/                # Audio processing library
    └── simple_recorder.rs         # Basic audio implementation

Installation

  1. Clone the main repository:

    git clone <repository-url>
    cd meeting-minutes
    
  2. Clone screenpipe (required for audio capture):

    cd experiment
    git clone https://github.com/mediar-ai/screenpipe.git
    cd rust_based_implementation
    
  3. Install dependencies:

    pnpm install
    

Running the App

Use the provided script to run the app:

./clean_build.sh

This script will:

  1. Install dependencies
  2. Check for and download the Whisper model if needed
  3. Start the Whisper server
  4. Launch the Tauri app in development mode

Implementation Details

This implementation differs from the main project by:

  • Using Rust instead of Python for the backend
  • Using Tauri instead of Electron for desktop integration
  • Running Whisper locally instead of using external APIs
  • Implementing real-time audio processing in Rust
  • Using the screenpipe library for audio capture

Development Status

This is an experimental implementation that explores:

  • Using Rust for better performance in audio processing
  • Native desktop integration with Tauri
  • Local transcription with Whisper
  • Real-time audio processing capabilities

For the production implementation, please see the main project in the root directory.

Contributing

  1. Fork the repository
  2. Create your feature branch (git checkout -b feature/amazing-feature)
  3. Commit your changes (git commit -m 'Add some amazing feature')
  4. Push to the branch (git push origin feature/amazing-feature)
  5. Open a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

马建仓 AI 助手
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